The present invention is directed to positioning and navigation systems.
Positioning and navigation systems are used in a wide range of applications. One particular application that presents unique challenges is in connection with robots or unmanned vehicles. Currently, a global positioning system (GPS) is virtually the only technique used for robot positioning in outdoor applications. Developments in this field have been made to accommodate the accuracy and limitations of GPS. When GPS capability is denied due to signal reception difficulties, then these devices turn to inertial navigation system (INS) techniques. A GPS/INS positioning system is expensive and achieves precise navigation only when a significant view of the GPS satellites exists from time to time. Moreover, it is still necessary to employ a source of differential GPS correction data from a radio transmitter station in communication with the vehicle. Furthermore, INS systems accrue error as a function of time because they use acceleration sensors to calculate position displacement through integration. Therefore, every minute that a GPS/INS-based system does not see enough sky to cancel out the INS error, the position accuracy of the vehicle continues to worsen.
Dead reckoning is a technique used to update position during periods of “blackout” of the absolute positioning system (e.g., GPS). This may be achieved by sensing the relative movement of the vehicle as it moves about. INS techniques may be used to determine relative movement, but odometry is often used instead of INS for dead reckoning. The sources of error with odometry are the uncertainty in the direction of motion at any instant and slippage of the vehicle's wheels on the terrain. Dead reckoning error is commonly specified as percent error versus distance traveled and two percent dead reckoning error is considered very good. Thus, for applications that require very precise positioning determinations, it is not tolerable to have blackouts in the absolute positioning system.
Numerous positioning system approaches are known that attempt to provide accurate mobile robot positioning without the use of GPS. These approaches include GPS-pseudolite transmitters, RF beacons, ultrasonic positioning, active beam scanning and landmark navigation. In particular, a landmark navigation system uses a sensor, usually a camera, to determine a vehicle's position and orientation with respect to artificial or natural landmarks. Artificial landmarks may be deployed at known locations and in current systems heretofore known take the form of a high contrast bar code or dot pattern. A sensor device can observe both the orientation and distance to the landmark so that only two landmarks need to be viewed in order to compute the vehicle's position. The challenge in a landmark navigation system is in reliably identifying the landmarks in cluttered scenes. The accuracy of the position computation is dependent on accurately determining the camera orientation to the landmark. Also, sufficient illumination is necessary with existing landmark navigation solutions.
Nevertheless, landmark navigation is attractive because of its potential for accuracy, high reliability, low cost and relative ease of deployment. There is, therefore, a need for an improved landmark navigation positioning system that can achieve the reliability and accuracy that current positioning system solutions for robotic or unmanned vehicles cannot.